Project Description

IMPROVING PATIENT EXPERIENCE IN THE EMERGENCY ROOM
WITH WAITING TIME MONITORS BY DEPARTMENT SPECIALTY

ZUYDERLAND

BRIEF

Waiting for medical help in an unexpected situation can be one of the most stressful and frustrating experiences that patients and their loved ones go through. It’s common for individuals to feel anxious and, in some cases, exhibit violent behaviors. To help ease their minds a bit, Zuyderland, a hospital in South Limburg, decided to introduce an innovative solution to improve the patient experience.

The idea was to develop monitors that visualize the expected waiting time in the emergency room. These kinds of monitors already exist in several Dutch hospitals, so what’s so special about this solution? Zuyderland decided to go a step further and provide patients with a waiting time monitor per department specialty based on a data model, now that’s a unique and innovative feature! During the development of this solution, our Data Science expert worked closely with Zuyderland to lay the groundwork and supported them with:

  • Data preparation
  • Developing a suitable statistical model

  • Domain knowledge and expertise

  • A working prototype of the monitor

THE CONCEPT

In the past, patients had no idea what was going on behind the scenes, but now they get a better idea of how busy it is. Based on the crowdedness of the emergency room, patients now have a better grasp of how much time they will spend waiting for treatment. Moreover, to safeguard their privacy, the calculated waiting time spans only from the moment they enter the emergency room until they begin receiving treatment.

CUSTOMER CHALLENGE

The first challenge was to collect data from the SAP system and transform it in near real-time to provide up-to-date information. Next, we worked on developing a statistical model to accurately represent real-time conditions of the emergency room. This model takes into account the number of people currently in the ER to estimate how long a new patient has to wait. This step is complex because the data must be both accurate and up-to-date. There are cases where the data is not complete — for example, a patient still in the waiting room may not have all their data entered, or some essential information might not be logged until later, leading to incomplete data that must be managed. To deal with this, the statistical model is designed to set a maximum expected waiting time. This helps in setting realistic expectations for patients. Finally, in-depth knowledge of the medical domain is crucial to this project to ensure high quality data.

TECHNIQUES AND TECHNOLOGIES

This project required a close collaboration between the Data Science expert from Mediaan and Zuyderland. During this project the following methods and technologies were used:

  • Microsoft SQL
  • Pyhton

  • Statistical Modeling
  • Machine Learning
  • PowerBI

RESULTS

The provided solution retrieves data every five minutes, depending on the type of patients and specialties. The created model incorporates a comprehensive analysis of patient flow patterns, taking into account the influx data from the past two years. This historical insight, combined with real-time updates, provides patients with a transparent and reliable estimation of their waiting times. Overall, this innovative solution has significantly improved the patient experience in the ER.

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